Week 1: Introduction¶

POP77001 Computer Programming for Social Scientists¶

Tom Paskhalis¶

12 September 2022¶
Module website: tinyurl.com/POP77001¶

Overview¶

  • Module objectives
  • Prerequisites and software
  • Materials and books
  • Module meetings
  • Assessment and collaboration
  • Weekly schedule

Source: Harvard Business Review

Source: Drew Conway

Source: Reddit

About me¶

  • Assistant Professor in Political Science and Data Science, Trinity College Dublin
    • Before: Postdoctoral Fellow, New York University
    • PhD in Social Research Methods, London School of Economics and Political Science
  • My research:
    • Political communication, social media, interest groups
    • Text analysis, machine learning, record linkage, data visualization
  • Contact
    • tom.paskhalis@tcd.ie
    • tom.paskhal.is
    • @tpaskhalis

Module Objectives¶

  • Introduce the fundamentals of computer programming;
  • Get familiar with R and Python programming languages;
  • Develop understanding of core software design principles;
  • Learn crucial data science techniques;
  • Practice these concepts using social science examples.

Module Materials¶

  • Course website: tinyurl.com/POP77001
  • GitHub repository: github.com/ASDS-TCD/POP77001_Computer_Programming_2022

Books¶

  • Guttag, John. 2021 Introduction to Computation and Programming Using Python: With Application to Computational Modeling and Understanding Data. 3rd ed. Cambridge, MA: The MIT Press

  • Matloff, Norman. 2011. The Art of R Programming: A Tour of Statistical Software Design. San Francisco, CA: No Starch Press.

  • McKinney, Wes. 2017. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 2nd ed. Sebastopol, CA: O'Reilly Media

  • Roger D. Peng. 2016. R Programming for Data Science. Leanpub.

  • Wickham, Hadley, and Garrett Grolemund. 2017. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Sebastopol, CA: O'Reilly Media.

  • Wickham, Hadley. 2019. Advanced R. 2nd ed. Boca Raton, FL: Chapman and Hall/CRC.

Additional Online Materials¶

  • Git Book

  • The Hitchhiker's Guide to Python

  • Python For You and Me

  • Python Wikibook

  • Python 3 Documentation

  • R Documentation

  • R Inferno

Prerequisites and Software¶

  • Introductory module - no formal prerequisites
  • Laptop with Windows/Mac/Linux OS (no Chrome books)
  • Required software:
    • Jupyter - web-based interactive computational environment
    • Python (version 3+) - versatile programming language
    • R (version 4+) - statistical programming language
  • Additional software:
    • Git - version control system
    • GitHub - git-based online platform for code hosting
    • RStudio - integrated development environment for R
    • Spyder - integrated development environment for Python
    • Visual Studio Code - feature-rich text editor

Module Meetings¶

  • 11 two-hour lectures
    • Monday 14:00 in PX 201 7-9 Leinster Street South
  • 11 two-hour tutorials
    • Wednesday 14:00 in PX 201 7-9 Leinster Street South
  • No lecture/tutorial in Week 7
  • Office hours:
    • Thusday 11:00 - 13:00 online

Assessment¶

  • Participation (10 %)

    • Tutorial attendance

  • 4 assignments (40%)

    • Bi-weekly programming exercises
    • Due by 23:59 on Friday of weeks 3, 5, 9 and 11 on Blackboard

  • Final project (50%)

    • Final R/Python project demonstrating familiarity with programming concepts and ability to communicate results
    • Due by 23:59 on Friday, 16 December 2022

Assessment criteria¶

  1. ✔️ Code exists
  2. ⌚ Code runs and does what it has to do
  3. 📜 Code is legible (meaningful naming, comments)
  4. ⚙️ Code is modular (no redundacies, use of abstractions)
  5. 🏎️ Code is optimized (no needless loops, runs fast)

Marks at Trinity: https://www.tcd.ie/academicregistry/exams/student-guide/

Plagiarism¶

  • Plagiarising computer code is as serious as plagiarising text (see Google LLC v. Oracle America, Inc.)
  • All submitted programming assignments and final project should be done individually;
  • You may discuss general approaches to solutions with your peers;
  • But do not share or view each others code;
  • You can use online resources but give credit in the comments.

Module Outline¶

Week Language Topic Assignment Due
1 - Introduction to Computation
2 R R Basics
3 R Control Flow in R Assignment 1
4 R Functions in R
5 R Debugging and Testing in R Assignment 2
6 R Data Wrangling in R
7 - -
8 Python Fundamentals of Python Programming I
9 Python Fundamentals of Python Programming II Assignment 3
10 Python Data Wrangling in Python
11 Python, R Complexity and Performance Assignment 4
12 Python, R Web Scraping

Next¶

  • Introduction to Computation